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It didn’t have to be this way. SARS appeared in 2003. Since then there has been a lot of research, and some previous “warning shots” (MERS, 2012) that clearly said “get ready.” But it’s worse than that: after 9/11, the potential for biological warfare based terrorism was a extensively studied and considered. Money was spent, plans were suggested, little action was taken. So at least three administrations have dropped the ball on pandemic planning (and those plans that did exist were largely ignored). Even worse was what has happened this year. We had over two months of solid intel (and credible reports of more than three) that something bad was on the way. The present administration did virtually nothing. The Congress, who gets much of the same intel, did nothing. Yes, Presidential leadership would have been optimal, and President Trump’s administration Failed, but I didn’t see reports of stacks of legislation being sent to his desk, and much of a response would have had to come from the legislative end of Pennsylvania Ave. So in short, the Legislative and Executive branches of the US Government, both political parties, failed the American people. Very little can be argued about that except by die hard partisans.

Next, after the gross under-reaction, there was an arguable overreaction in some ways. Measured, targeted approaches of shutting down “high contact” activities while preserving other less risky commercial activities were not taken: a one size fits all “shut it all down” approach was the norm – cause in part by the lack of testing and/or plans. States imposed their will on municipalities, when stronger or weaker measures may have been appropriate depending on the locale. But politics aside, those kinds of targeted actions require technical things that the US just doesn’t have: a coherent and reliable testing, tracking, and isolation system.

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The question of the week is if Georgia and other states should be reopening. Naturally the response of most people breaks down over predictable political lines, but lets see if we can learn anything from looking at actual data. The key question is if the available data shows that the spread is contained. And that means looking at testing data. As noted previously there are good reasons to be very suspicious about some of the testing in terms of timeliness and quality. But let’s assume the testing data can be taken at face value and see what it tells us. First, how widespread is testing? Not very. Here’s a plot of testing by day for Georgia, New York, Michigan, and Washington State. Pretty depressing: they are all under 4% of the total population. That’s insane considering that the SARS-COV-2 virus could have already spread to 5 to 40% of the country by some estimates …

Georgia is last, well under 1%. But, if the virus isn’t widespread and is contained, that’s not inherently a problem. If you’re testing lots of people, and those people are not getting sick or are negative, then you’ve expanded your testing outside the group of sick people and can be reasonable sure that you’ve got a handle on things. If the positive to total ratio is under 10% I would start to be comfortable. A great sign is if that number is starting to trend sharply down over time (eg the more you test, the more negatives you find). Let’s see what that looks like … Continue reading →

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I see a lot of people who are viewing the economic impacts of the SARS-COV-2 outbreak as an opportunity for change. Across the political spectrum activists for various causes are practically salivating over the opportunity to use the crisis to implement their favorite agendas.

Climate change? Great! The crashing oil markets are the perfect time to act!

Social Justice? Great! The economic and health system disparities made clear by the virus are the perfect time to act!

Iran? Great! Their weakened state, internal unrest, along with the insulation of a down oil market, make this the perfect time to act!

China? Great! Their weakened state, internal unrest, anger over their handling of the the crisis make this the perfect time to act!

The list seems endless. And all of those forces are interacting in the political process, slowing down economic interventions in the real economy (the Fed and other reserve banks are propping up the markets, but I hope most people realize that the stock and bond markets are no longer much related to the real economy). There’s just one problem: all of the potential for change is potentially delusional.

It seems pretty obvious that the global political and economic system is on the verge of a cascading collapse, probably merely weeks or at best months away. I have discussed this with several colleagues, and while we are coming at it from different directions (some from economics, some from geopolitics) we end up in the same place. And that should give everyone some pause. What will be the trigger? There so many to choose from it’s hard to say. In the US, tens of thousands of small businesses are on the verge of failure. Those businesses all have mortgages, pay rents, pay taxes, buy stuff from other businesses – as do their employees. Once those go, the domino effect (zipper effect, whatever you want to call it) will rapidly lock up or even collapse the entire financial system, especially state and local governments dependent on tax revenues. Consider one small, often overlooked aspect: that welfare benefits are distributed using the Electronic Benefit Transfer (EBT) system. That uses debit cards to provide benefits to recipients. What happens if banks stop extending credit and the electronic money system becomes restrictive or locks up? What happens if grocery stores can’t accept EBTdue to their own credit issues or delays in state payments? Millions of people in the US would suddenly be cut off. In areas where the EBT has been disrupted for even 24-48 hours, social unrest (rioting, looting, etc) has rapidly ensued. That these happened in isolated, urban high crime areas means they didn’t capture the public attention, but if that happens nationally … well, it will be ugly. I could terrify you with various geopolitical scenarios as well. Most of these are of “low” probability (some 1 in 5, some 1 in 10), but when you have a bunch of “low” probability events, the chances of one of them happening start to approach 1.0. And they all end up in the same place: something happens that causes the fragile, overly interconnected and over leveraged credit and financial system to go into a death spiral. Once it happens, it will be hard or impossible to stop, given that if any one “trigger” happens, like a string of firecrackers it will set the others off. So that brings us to this:

There isn’t time to use this crisis to craft some wonderful transition to a brave new (Marxist, Progressive, Green, NeoCapitalist, ‘Murican!, Libertarian, whatever) world. We have to stop the collapse at all costs and buy time. Or none of those things will mean anything. The Congress is set to pass a boost in funding to the Paycheck Protection Program and some other tweaks today. It is woefully inadequate by an order of magnitude (trillions are needed, not hundreds of billions). Even re-opening is not likely to help at this stage (even assuming there are not repercussions or fall “second wave”).

If the system collapses, no matter what the trigger, there won’t be any opportunities for change. Yes, we need to move to something more sustainable. If we get past this crisis that will take on even more urgency because it is doubtful we will get another chance. To use a medical analogy, the patient is in about to go into cardiac arrest; we can worry about diet and exercise when we get the heart beating again. But for now, we need to stop pushing for the next thing until we can have some confidence there will even be a next thing …

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Bold headline – better have some numbers to back it up. OK: Two different calculations ended up with the same conclusion that the US State of Georgia, which yesterday decided to start relaxing mitigation guidelines, is very likely undercounting or under-reporting COVID-19 deaths by on the order of 30%. Let’s see why this outrageous statement was made. I will keep the math and statistics light here; may try to do another post with the detailed calculations for those who are curious when I get more time to write it up.

First, a disclaimer: the data for the State of Georgia is problematic (wretched, abysmal, horrific, consult your thesaurus and pick your favorite adjective). Consider: For the week ending April 4th (that was now over two weeks ago), Georgia has only managed to report 66.8% of its death data to the NCHS Pneumonia and Influenza surveillance system. Three weeks ago, that number is up to 87.7%. I’m doing comparisons with the state of Washington in this analysis, since the claimed curves seem similar, and the populations are of similar size (7.8 Million for Washington, 10 million for Georgia). Now, that’s really unfair, because by most health care quality of life metrics, Washington State should be “better”, but on the other hand, Georgia’s CFR is 3.993% vs Washington’s 5.308%, and Georgia says it’s ready to re-open whereas Washington is being more cautious.

Oh, and what are the Washington reporting statistics? 100% for the week of March 28. 100% for the week of April 4th. Hmmm …

So, with that background, lets try to back out what Georgia’s numbers should be.

Method 1: Case Fatality Rates

As noted, I really don’t like CFR’s. They are really noisy given the testing environment. But sometimes it’s all you have. At similar points in the curve (Washington State should be “ahead” of Georgia by at least 10 days), we should be seeing similar CFR’s, all things being equal (and they probably aren’t, given difference in demographics, aggressive early action, etc, all of which are in Washington State’s favor, so this give a huge “advantage” to Georgia). The Washington CFR is 5.0% at the point in the curve where Georgia is today, yet Georgia is reporting only 3.9%, or a 28% lower rate. Applying that to the most recent report, Georgia should be showing 994 deaths rather than the 775 it is in fact reporting. If we use the smoothed end point CFR, it’s even larger, 1030 vs 775 (32.9%).

Method 2: Pneumonia Death Rates

This method is a bit more complex. It involves analyzing the NCHS Pneumonia and Influenza (P&I) death surveillance system and computing “excess” mortality. A key problem is that Georgia takes a long time to report death data under normal circumstances. COVID-19 is moving so fast, using data from a couple of weeks ago is making a noisy situation even more noisy. But, with that yuge caveat, we can dive in. I’ll spare you a lot of math here, but the bottom line is adjusting for where we are in the season, the reported P&I and Influenza deaths, etc. the Washington State data matches their reported COVID19 deaths pretty well – 127 reported, 129 predicted. Georgia dosen’t. The reported is 132, the predicted 170 – a 29% undercount.

Conclusion and Opinion

It is widely suspected that the excess mortality from COVID-19 has been underestimated. When you dig in to cases and fatalities for the US state of Georgia, they just seem anomalous, even given the normal noise in these kinds of data sets. In comparison to other states and countries, the numbers just don’t add up. Even so, based on that data, there is no evidence that Georgia has reached a point in the curve where mitigation measures should be reassessed. Testing is still problematic, and the reporting is highly questionable (likely a result of both the well publicized problems in testing and long standing delays in public heath reporting statistics). Maybe things are better than the data shows. But there is no way to know that – it’s just guessing and hope. But Hope isn’t a Plan. The Governor is doing a massive experiment with the lives of the people of the state. I hope he’s right; I’m afraid he’s wrong.

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To continue the previous point that the COVID-19 data is problematic (scientific word for “sucks”), the results over the last few days just reinforces the fact that doing quantitative analysis on something where the quality is so bad is frustrating at best, and misleading at worst. And that has enormous policy implications.

Why is this? We need to know at least three key values to get a handle on this pandemic:

The number of people who have died from it (how bad is it?);

The number of people who got it and were spreading it (how infectious is it?);

The total number of people who have been exposed to it to a sufficient degree to either beat it or got sick (how far along in the pandemic we are?).

There are some other “great to know” data points, but these are the absolutely essential numbers we need to have at least some level of confidence in to decide things like what mitigation measures are required, if the pandemic is tapering off,, and when (and under what conditions) it is safe to “reopen”. The problem is we should have almost zero confidence in any of these three numbers.

Take something ‘simple’ like the number of people who have died. Should be simple: someone died from an ACUTE onset respiratory disease. You test for the SARS-COV-2 virus, and if that is positive, you can call it COVID-19. This is vital to have nailed down, because that tells us how bad this thing is. Yet we don’t know that number with any degree of confidence. As noted previously, the testing situation is a nightmare and getting worse, not better. There hasn’t been enough testing, so in many cases the diagnosis is based only on symptoms. The testing itself is problematic, and the newer, fast tests are of really dubious accuracy (as bad as only 30% by some studies). There are no universally applied standards, and no uniformly collected and available data sets, for what is and isn’t a SARS-COV-2 primary cause of death.

So the bottom line is that plots like this:

showing the deaths per 10,000 people, are nearly worthless for decision making at this point. Look at what happened to the New York numbers last week, when they arbitrarily changed their selection criteria. The other two via questions, how many people have it and are actively spreading it, much less how many have already been exposed and beaten it, are even less usable: no reliable testing, no standardized criteria. That’s not to say we can’t extrapolate, interpolate, and try to draw some actionable conclusions – we have to do that no matter how bad the data. I’ts just that this data is way noisier than it should be, and thus the decision making is far more uncertain and risky than it needs to be.

This is the sad and embarrassing situation in the US. Other western countries like Iceland, Denmark, Germany are in vastly better shape with respect to what is going on. The US, despite much greater resources, is a mess due to a fragmented political structures (local vs. states vs federal), and the convoluted health care delivery system.

And no reliable information means that decisions are arbitrary and driven by politics, not science. And before one side or the other claims the mantle of “good science”, that applies to both parties – the shoddy foundation for this sad situation has been laid by administrations of both parties over the last 40 years. There was an opportunity, after the end of the Cold War, to take care of many social and structural issues that had been subsumed by that conflict. Instead, both parties squandered the opportunity. Disasters like this were, and are, inevitable.

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One of my secondary areas of research is how information flows during a crisis. As noted previously, how people act is based on their perception of reality, not the actual state of things, and so for modeling purposes you have to model what people think is going on – as well as what is actually going on – in order to anticipate their actions. The situation in Savannah, GA, where I am based, is a snapshot of what is going on in communities across the nation – and world for that matter. Unfortunately, the lack of trust in institutions, especially government and the news media, has become reminiscent of the former Soviet Union and rumors are often taken as fact. And here in Savannah, there are some pretty toxic rumors floating around, some originating in the health care community. Please read this post to the end; it’s important!

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Good information is vital for decision making. With respect to the ongoing pandemic, leaders and internet experts alike in the US are analyzing the numbers, doing projections, making plans, not to mention news outlets scaring the poop out of people with “death counters” and “breaking news” of new numbers. There is just one problem: all of this is based on numbers that are so noisy they are almost useless. And there are powerful political forces in both “tribes” driving the data in to places it doesn’t want to go – something much easier to do with bad data.

Yes, often you have to work with data that is noisy. Experts do it all the time. But I can’t recall seeing so much analysis, decisions, and opinions rendered on vital subjects on data that is so crappy – often by people with little to no experience in dealing with noisy data.

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In many parts of Europe, there seems to be a light at the end of the tunnel. Denmark (added to the chart), which took early action, is reopening schools and day care for kids under 11, as it appears their response has things under control. It is interesting to compare the Denmark, Norway, Sweden, and Denmark, as each took different approaches to societal restrictions. I’m sure many papers will be written! Spain seems to have hit the inflection point of their curve, but while cases are down, the death rate in Italy continues to climb. This might be a data and recording problem – their system was so overwhelmed deaths are just now being recorded that happened days ago.

In the US, it’s hard to tell what is going on. Testing and data tracking in this country is an embarrassment for a so called developed country. Continue reading →

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One of the problems with a 24 hour infotainment (aka news) cycle is that there is constant pressure to come up with “new content.” If I don’t post something for a day or so I get messages from the usual social media suspects that “your thousands of followers haven’t heard from you in a while, write something!” Honestly, given my research subjects, I think most of my followers are perfectly happy NOT hearing from me. But if you’re in the professional content business you have your kleptocaptialist corporate masters to serve, so you have to come up with something. So you do. Even if it’s more trivia than information or news – the more inflammatory the better. So, if deaths are down in one area, play them up in another. The political shenanigans are always great for hits, and politicians are always looking for a camera to love. “Things are moving along as predicted, hang in there, nothing new to report” just doesn’t sell the latest prescription drugs (insert rant here).

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Yesterday the respected Institute for Health Metrics and Evaluation (IHME) at the University of Washington released an updated model of COVID and various projections. Their current estimate for total US deaths is down to 60415, down from over 93,000 last week. The reason given for the drop is a combination of better data and the impacts of mitigation measures like travel restrictions and “social distancing.” This is a long post, the latest data and models are worth taking a close look as there is both good news and bad.

A couple of caveats about this estimate. First, it is only through August, so additional deaths after that are not included. Second, it may be overestimating the impact of the mitigation measures. Finally, it assumes the mitigation measures will remain in place for longer than they are presently scheduled to do so. My guess is that the next revision will be upwards, but we’ll see. For what it’s worth, my “in house” statistical model is a bit higher, at 72,820. For perspective, note these total numbers are very similar to the toll from the H3N2 outbreak in 2017 (61000), and less than the Sydney Flu of the late 1990’s (114,526). Of course, as previously noted, while this virus may end up with a similar death toll to influenza, the rate of deaths are five or six times faster.